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Abstract #155656

Stephanie Ball, MPH, Department of Environmental Health Sciences, University of Minnesota, MMC 807, 420 Delaware St., Minneapolis, MN 55455, 202-302-5877, ballx065@umn.edu and Randall Singer, DVM, PHD, Department of Veterinary and Biomedical Sciences and the Department of Environmental Health, University of Minnesota, 1971 Commonwealth Ave., St. Paul, MN 55108.

Antibiotic resistance is a growing issue in the clinical treatment of severe Salmonella spp infections in the United States. A large proportion of Salmonella infections are contracted through contaminated meat products. A recent study revealed that there exist a large variety of serotypes and antimicrobial resistance patterns in Salmonella isolates recovered from retail meat; among the 365 isolates there were 175 distinct PFGE patterns. This project used data from the Iowa retail meat study to assess the representativness of the sampling scheme currently employed by the FDA.

Data for this study have been provided by the US Food and Drug Administration; the data is a subset of data collected during the Iowa retail meat study. An iterative Markov Chain Monte Carlo method is used to model the various antimicrobial resistance patterns found among the isolates and the variety of patterns seen across various cultivation media used in the laboratory. Several models are tested that attempt to discern the role that different media play in the manifestation of resistance patterns seen in the laboratory.

This analysis helps to determine whether federal antimicrobial resistance monitoring programs are testing enough meat samples and Salmonella isolates per meat sample to adequately predict the antibiotic resistance patterns seen in clinical salmonellosis. This analysis also contributes to the growing body of knowledge being used to conduct quantitative microbial risk assessments.

Learning Objectives:

• Apply bayesian modeling to issues in food-borne disease
• Analyze a model that will determine the validity of sampling methodology
• Recognize the value of valid prevelance measurements of antimicrobial resistance in constructing quantitative risk assessments

Keywords: Antibiotic Resistance, Food Safety

Presenting author's disclosure statement:

Any relevant financial relationships? No
Any institutionally-contracted trials related to this submission?

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.